CRAN/E | mlr3spatiotempcv

mlr3spatiotempcv

Spatiotemporal Resampling Methods for 'mlr3'

Installation

About

Extends the mlr3 ML framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored.

mlr3spatiotempcv.mlr-org.com/
github.com/mlr-org/mlr3spatiotempcv
mlr3book.mlr-org.com
Bug report File report

Key Metrics

Version 2.3.1
R ≥ 3.5.0
Published 2024-04-17 3 days ago
Needs compilation? no
License LGPL-3
CRAN checks mlr3spatiotempcv results

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Maintainer

Maintainer

Patrick Schratz

patrick.schratz@gmail.com

Authors

Patrick Schratz

aut / cre

Marc Becker

aut

Jannes Muenchow

ctb

Michel Lang

ctb

Material

README
NEWS
Reference manual
Package source

In Views

Spatial
SpatioTemporal

Vignettes

Getting Started
Spatiotemporal Visualization

macOS

r-prerel

arm64

r-release

arm64

r-oldrel

arm64

r-prerel

x86_64

r-release

x86_64

Windows

r-prerel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

mlr3spatiotempcv archive

Depends

mlr3 ≥ 0.12.0
R ≥ 3.5.0

Imports

checkmate
data.table
ggplot2 ≥ 3.4.0
mlr3misc ≥0.11.0
paradox
R6
utils

Suggests

bbotk
blockCV ≥ 3.1.2
caret
CAST ≥ 0.8.0
ggsci
ggtext
here
knitr
lgr
mlr3filters ≥ 0.7.0.9000
mlr3pipelines
mlr3spatial
mlr3tuning
patchwork
plotly
rmarkdown
rpart
sf
sperrorest
terra
testthat ≥ 3.0.0
twosamples
vdiffr ≥ 1.0.0
withr